What Integrates with Flowise?

Find out what Flowise integrations exist in 2024. Learn what software and services currently integrate with Flowise, and sort them by reviews, cost, features, and more. Below is a list of products that Flowise currently integrates with:

  • 1
    OpenAI Reviews
    OpenAI's mission, which is to ensure artificial general intelligence (AGI), benefits all people. This refers to highly autonomous systems that outperform humans in most economically valuable work. While we will try to build safe and useful AGI, we will also consider our mission accomplished if others are able to do the same. Our API can be used to perform any language task, including summarization, sentiment analysis and content generation. You can specify your task in English or use a few examples. Our constantly improving AI technology is available to you with a simple integration. These sample completions will show you how to integrate with the API.
  • 2
    Langfuse Reviews

    Langfuse

    Langfuse

    $29/month
    1 Rating
    Langfuse is a free and open-source LLM engineering platform that helps teams to debug, analyze, and iterate their LLM Applications. Observability: Incorporate Langfuse into your app to start ingesting traces. Langfuse UI : inspect and debug complex logs, user sessions and user sessions Langfuse Prompts: Manage versions, deploy prompts and manage prompts within Langfuse Analytics: Track metrics such as cost, latency and quality (LLM) to gain insights through dashboards & data exports Evals: Calculate and collect scores for your LLM completions Experiments: Track app behavior and test it before deploying new versions Why Langfuse? - Open source - Models and frameworks are agnostic - Built for production - Incrementally adaptable - Start with a single LLM or integration call, then expand to the full tracing for complex chains/agents - Use GET to create downstream use cases and export the data
  • 3
    Docker Reviews

    Docker

    Docker

    $7 per month
    4 Ratings
    Docker eliminates repetitive, tedious configuration tasks and is used throughout development lifecycle for easy, portable, desktop, and cloud application development. Docker's complete end-to-end platform, which includes UIs CLIs, APIs, and security, is designed to work together throughout the entire application delivery cycle. Docker images can be used to quickly create your own applications on Windows or Mac. Create your multi-container application using Docker Compose. Docker can be integrated with your favorite tools in your development pipeline. Docker is compatible with all development tools, including GitHub, CircleCI, and VS Code. To run applications in any environment, package them as portable containers images. Use Docker Trusted Content to get Docker Official Images, images from Docker Verified Publishings, and more.
  • 4
    GitHub Reviews
    Top Pick

    GitHub

    GitHub

    $7 per month
    22 Ratings
    GitHub is the most trusted, secure, and scalable developer platform in the world. Join millions of developers and businesses who are creating the software that powers the world. Get the best tools, support and services to help you build with the most innovative communities in the world. There's a free option for managing multiple contributors: GitHub Team Open Source. We also have GitHub Sponsors that help you fund your work. The Pack is back. We have partnered to provide teachers and students free access to the most powerful developer tools for the school year. Work for a government-recognized nonprofit, association, or 501(c)(3)? Receive a discount Organization account through us.
  • 5
    Hugging Face Reviews

    Hugging Face

    Hugging Face

    $9 per month
    AutoTrain is a new way to automatically evaluate, deploy and train state-of-the art Machine Learning models. AutoTrain, seamlessly integrated into the Hugging Face ecosystem, is an automated way to develop and deploy state of-the-art Machine Learning model. Your account is protected from all data, including your training data. All data transfers are encrypted. Today's options include text classification, text scoring and entity recognition. Files in CSV, TSV, or JSON can be hosted anywhere. After training is completed, we delete all training data. Hugging Face also has an AI-generated content detection tool.
  • 6
    TypeScript Reviews

    TypeScript

    TypeScript

    Free
    TypeScript adds syntax to JavaScript to allow for tighter integration with your editor. Make sure to catch errors in your editor as soon as possible. TypeScript code can be converted to JavaScript and runs wherever JavaScript runs: in a browser, on Node.js, Deno, or in your apps. TypeScript can understand JavaScript and uses type-inference to provide great tooling for JavaScript without any additional code. 78% of 2020 State of JS respondents used TypeScript, and 93% said they would use it again. Type errors are the most common errors programmers make. A certain type of value was used when a different value was expected. This could be simple typos, failure to understand an API surface, incorrect assumptions about runtime behavior or other errors.
  • 7
    Chroma Reviews

    Chroma

    Chroma

    Free
    Chroma is an AI-native, open-source embedding system. Chroma provides all the tools needed to embeddings. Chroma is creating the database that learns. You can pick up an issue, create PRs, or join our Discord to let the community know your ideas.
  • 8
    Zep Reviews

    Zep

    Zep

    Free
    Zep will ensure that your assistant remembers previous conversations and brings them up when they are relevant. In milliseconds, you can identify your user's intention, create semantic routers and trigger events. Emails, phone number, dates, names and more are extracted quickly and accurately. Your assistant will never lose track of a user. Classify intent, emotions, and more, and convert dialog into structured data. Your users will never have to wait. We do not send your data to a third-party LLM service. SDKs for all your favorite frameworks and languages. Automatically populate prompts, no matter how far back they are, with a summary relevant past conversations. Zep summarizes and embeds your Assistant's chat logs. It then executes retrieval pipelines. Instantly and accurately categorize chat dialog. Understanding user intent and emotion. Route chains based upon semantic context and trigger events. Extract business data quickly from chat conversations.
  • 9
    Node.js Reviews
    Node.js is an asynchronous JavaScript runtime that drives JavaScript calls. It's designed to create scalable network applications. Node.js will go to sleep if there isn't any work being done. This is in contrast with the more common concurrency model today, where OS threads are used. Thread-based networking is slow and difficult to use. Node.js users are not at risk of deadlocking the process because there are no locks. Nearly every function in Node.js performs I/O. The process never blocks unless the I/O is performed using synchronous Node.js methods standard library. Scalable systems are easy to create in Node.js because nothing blocks. Node.js is inspired by and similar to Ruby's Event Machine, and Python's Twisted. Node.js extends the event model a little further. It presents an event loop instead of a library as a runtime construct.
  • 10
    JavaScript Reviews
    JavaScript is a web scripting language and programming language that allows developers to create dynamic elements on the internet. Client-side JavaScript is used by over 97% of all websites. JavaScript is the most popular scripting language on the internet.
  • 11
    LangChain Reviews
    We believe that the most effective and differentiated applications won't only call out via an API to a language model. LangChain supports several modules. We provide examples, how-to guides and reference docs for each module. Memory is the concept that a chain/agent calls can persist in its state. LangChain provides a standard interface to memory, a collection memory implementations and examples of agents/chains that use it. This module outlines best practices for combining language models with your own text data. Language models can often be more powerful than they are alone.
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